Designing and integrating composite networks for monitoring multivariate gaussian pollution fields

Networks of ambient monitoring stations are used to monitor environmental pollution fields such as those for acid rain and air pollution. Such stations provide regular measurements of pollutant concentrations. The networks are established for a variety of purposes at various times so often several stations measuring different subsets of pollutant concentrations can be found in compact geographical regions. The problem of statistically combining these disparate information sources into a single 'network' then arises. Capitalizing on the efficiencies so achieved can then lead to the secondary problem of extending this network. The subject of this paper is a set of 31 air pollution monitoring stations in southern Ontario. Each of these regularly measures a particular subset of ionic sulphate, sulphite, nitrite and ozone. However, this subset varies from station to station. For example only two stations measure all four. Some measure just one. We describe a Bayesian framework for integrating the measurements of these stations to yield a spatial predictive distribution for unmonitored sites and unmeasured concentrations at existing stations. Furthermore we show how this network can be extended by using an entropy maximization criterion. The methods assume that the multivariate response field being measured has a joint Gaussian distribution conditional on its mean and covariance function. A conjugate prior is used for these parameters, some of its hyperparameters being fitted empirically.     

Binary probability maps using a hidden conditional autoregressive Gaussian process with an application to Finnish common toad data

The Finnish common toad data of Heikkinen and Hogmander are reanalysed using an alternative fully Bayesian model that does not require a pseudolikelihood approximation and an alternative prior distribution for the true presence or absence status of toads in each 10 km×10 km square. Markov chain Monte Carlo methods are used to obtain posterior probability estimates of the square-specific presences of the common toad and these are presented as a map. The results are different from those of Heikkinen and Hogmander and we offer an explanation in terms of the prior used for square-specific presence of the toads. We suggest that our approach is more faithful to the data and avoids unnecessary confounding of effects. We demonstrate how to extend our model efficiently with square-specific covariates and illustrate this by introducing deterministic spatial changes.     

Integrated nested Laplace approximation for the analysis of count data via the combined model: A simulation study

The combined model accounts for different forms of extra-variability and has traditionally been applied in the likelihood framework, or in the Bayesian setting via Markov chain Monte Carlo. In this article, integrated nested Laplace approximation is investigated as an alternative estimation method for the combined model for count data, and compared with the former estimation techniques. Longitudinal, spatial, and multi-hierarchical data scenarios are investigated in three case studies as well as a simulation study. As a conclusion, integrated nested Laplace approximation provides fast and precise estimation, while avoiding convergence problems often seen when using Markov chain Monte Carlo.     

适应性网络空间抽样的设计及估计研究

随着大数据背景下抽样环境复杂化,特别是3S技术（遥感技术、地理信息系统和全球定位系统）日趋成熟,越来越多社会经济问题涉及空间抽样,其样本呈现出规模相对稀少、分布不均匀、局部聚集的特征,使得传统抽样调查面临着严重挑战。本文介绍了适应性抽样技术应用于空间网络环境的基本原理、主要操作步骤和马尔可夫链蒙特卡罗估计推断,并以广州市天河区的商户抽样为例讨论实际操作中应注意的问题,以期为流动人口、环境污染、区域经济研究等方面调查提供理论支撑和实证方法参考。     

Approximate composite marginal likelihood inference in spatial generalized linear mixed models

Non-Gaussian spatial responses are usually modeled using spatial generalized linear mixed model with spatial random effects. The likelihood function of this model cannot usually be given in a closed form, thus the maximum likelihood approach is very challenging. There are numerical ways to maximize the likelihood function, such as Monte Carlo Expectation Maximization and Quadrature Pairwise Expectation Maximization algorithms. They can be applied but may in such cases be computationally very slow or even prohibitive. Gauss–Hermite quadrature approximation only suitable for low-dimensional latent variables and its accuracy depends on the number of quadrature points. Here, we propose a new approximate pairwise maximum likelihood method to the inference of the spatial generalized linear mixed model. This approximate method is fast and deterministic, using no sampling-based strategies. The performance of the proposed method is illustrated through two simulation examples and practical aspects are investigated through a case study on a rainfall data set.     

河北省城市化发展路径分析

为加快推进河北省城市化战略的实施,本文提出了加强产业园区建设,优化城市总体布局,加快市政公用事业的市场化进程,消除农民进城的各种制度障碍的政策性思路。     

论聚居环境规划设计中的“曲”与“直”

以人类聚居环境建设为背景,通过对规划设计中"曲""直"不同层面的对比,分析由于观念问题所导致的认识上的偏差。从价值观念角度出发,探讨以"曲"为象征规划设计的深层内涵,提出其在人类聚居环境建设中的充分性和必要性。     

Residential mobility and the spatial dispersion of personal networks: Effects on social support

Using a representative national sample of personal networks, this article explores how the spatial dispersion of networks, residential mobility and social support are linked. Three issues will be addressed here. Firstly, how is the spatial dispersion of personal networks related to individuals’ social characteristics, network composition and residential mobility? Secondly, how do the spatial dispersion of networks, residential mobility and their combined effect influence the number and (thirdly) the structure of emotional support ties? Results showed that the extent of the support was affected neither by the geographical distribution of the networks nor by residential mobility. Living far from one's birthplace, however, exerted two distinct, and opposite effects on the support network structure. On the one hand, mobility led to high spatial dispersion of personal contacts, which in turn favored a sparsely knit network centered around the mobile individual. On the other hand, by controlling for the effect of distance between the contacts, we found that individuals that cited long-distance ties tended to be part of more transitive support networks than those that cited local ties. We interpreted the latter effect as evidence that transitive ties may survive greater spatial distances than intransitive ones. These findings are discussed in view of spatial mobility and social network research.     

The New Spatial Planning Act in Taiwan: A Messy Shift from Economic Development-Oriented Planning to Environmental Conservation-Oriented Planning?

On 18 December 2015, the spatial planning bill was finally passed by the Legislative Yuan in Taiwan. That was a special moment for planning community and authority since they had anticipated this moment for more than two decades. However, this is not the end of the story. On the contrary, the battle between the economic development promoters and environmental conservation supporters just starts. The Act introduces several new changes to secure its goal of nationwide sustainable development, but the introduction also raises some tensions. This article reviews the tensions and their socio-political context, and gives some suggestions to the Taiwanese government.     

中国各地区市场化进程区位分布的空间效应研究

 本文从空间分析的角度研究各地区市场化进程的空间效应及其对区域经济增长绩效的影响,空间计量经济分析的结果表明市场化进程的空间分布在整个样本区间与GDP、资本和劳动一样呈现出集聚的趋势,区域差异显著,各地区的市场化进程在地理空间上存在显著的自相关关系,证实了各地区市场化进程存在制度溢出效应。因此,在研究各地区市场化进程与经济增长关系时必须考虑其空间效应的影响,基于此结论本文运用空间计量模型测算了各地区市场化进程对经济增长的贡献。结果证实,考虑了空间效应后,市场化进程在1998～2001年阶段对经济增长的贡献约为6.2％,在2002～2005年阶段约为10.8％,这表明了市场化对中国的经济增长起到了重要的作用,而且近年来的贡献愈加显著。